Improved least squares identification

DOI10.1080/00207178708934023zbMath0638.93074OpenAlexW2022075676MaRDI QIDQ3780972

D. Grant Fisher, N. Rao Sripada

Publication date: 1987

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207178708934023

zbMATH Keywords

robustnessforgetting factorlow-pass filteringdata scalingrecursive least-squares (RLS) algorithm

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12) Numerical methods for initial value problems involving ordinary differential equations (65L05)

Related Items

Development and evaluation of an auto-tuning and adaptive PID controller, An augmented UD identification algorithm, Non-linear system identification using neural networks, Neural networks for nonlinear dynamic system modelling and identification, Adaptive control in the presence of markovian parameter jumps, Dynamics analysis, offline-online tuning and identification of base inertia parameters for the 3-DOF delta parallel robot under insufficient excitations, Recursive information forgetting with augmented UD identification, Identification of TAR models using recursive estimation, A robust model reference adaptive control for nonminimum phase systems, A robust model reference adaptive control for non-minimum phase systems with unknown or time-varying delay, Applicability of least-squares to the parameter estimation of large-scale no-memory linear composite systems, Multi-model parameter estimation scheme for self-tuning controllers, Convergence and stability of recursive damped least square algorithm, Formal proof for the constant trace forgetting factor

Cites Work

• Unnamed Item
• Unnamed Item
• Exponential convergence of recursive last squares with exponential forgetting factor
• Recursive estimation and time-series analysis. An introduction
• Practical issues in the implementation of self-tuning control
• Some design guidelines for discrete-time adaptive controllers
• Adaptive systems, lack of persistency of excitation and bursting phenomena
• Least squares parameter estimation
• Convergence analysis of recursive identification algorithms with forgetting factor
• System identification. A survey
• A stable adaptive predictive control system
• A new look at least-squares dynamic system identification
• A globally convergent adaptive pole placement algorithm without a persistency of excitation requirement